{"id":"W4242162962","doi":"10.1515/iupac.88.0527","title":"Avascularity","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Effects and risks of endocrine disrupting chemicals","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Philosophy; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001826452,0.001179701,0.001457447,0.006423585,0.0009117159,0.003977095,0.002132059,0.001525985,0.1975592],"category_scores_gemma":[0.02057584,0.0005758807,0.001630942,0.01023318,0.0005215533,0.003079724,0.003021679,0.001877632,0.1699081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001395601,"about_ca_system_score_gemma":0.003270958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008472896,"about_ca_topic_score_gemma":0.01646044,"domain_scores_codex":[0.9971151,0.000538044,0.0007040423,0.0007645889,0.0005965137,0.0002816718],"domain_scores_gemma":[0.9911384,0.003277048,0.001336158,0.001709779,0.002052961,0.000485629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000720379,0.000009871814,0.0007835747,0.002392501,0.00003149481,0.00002378641,0.00003530098,0.00007547175,0.00009701658,0.0009664157,0.9875098,0.008002683],"study_design_scores_gemma":[0.0000602603,0.000008924544,0.001425753,0.001111208,0.00002148895,0.0000492757,0.00004688424,0.00005734399,0.00009310628,0.0010403,0.9960709,0.00001460543],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001059105,0.0004198331,0.0001431417,0.0001911539,0.0001221735,0.00004058618,0.9952436,0.0002594157,0.00347425],"genre_scores_gemma":[0.0005350185,0.0005444928,0.0005808141,0.0003826921,0.00006047918,0.000263309,0.9948347,0.0001601779,0.002638355],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1975592,"threshold_uncertainty_score":0.6609015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01249425229283757,"score_gpt":0.4565202662215373,"score_spread":0.4440260139286997,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}